The CUDA page on Wikipedia includes a table listing Compute Capabilities. While verifying support for AMD Fiji GPUs, such as the Radeon Nano and FirePro S9300 X2, I became curious about how much functionality is still missing in OpenCL. After comparing…
Rant: No surprise there’s a shortage of good GPU-developers
We could read here that software is critical for HPC – a market where accelerators/GPUs are used a lot. So all we need to do is to better support all GPU-developers as a whole, not? Unfortunately something else is happening. Each…
4-day training on OpenCL-on-FPGAs, 24-28 October, Amsterdam
From 24 to 28 October we give a 4-day training on OpenCL-on-FPGAs using Altera hardware. The learning goals are correctly writing OpenCL code for FPGAs, learning to work with Quartus and understanding the important optimisation techniques. The total costs are €2760 excluding VAT for…
Porting code that uses random numbers
When we port software to the GPU or FPGA, testability is very important. A part of making the code testable, is getting its functionality fully under control. And you guessed already that run-time generated random numbers takes good attention. In a selection…
Random Numbers in Parallel Computing: Generation and Reproducibility (Part 2)
In the first part of our two-part blog series, we have discussed how parallel computing applications can best use pseudo-random number generators (PRNGs) so as to benefit from parallel computing speedups, without negatively impacting the statistical properties of the random numbers…
Strengthen our team as a remote worker (freelancer)
In the past year we’ve been working on more internal projects and therefore we’re seeking strong GPU-coders (good OpenCL experience required) worldwide. This way you can combine staying close to your family and working with advanced technologies. You will be on…